Estimate the diversity of species from abundance or probability data and a phylogenetic tree. Several estimators are available to deal with incomplete sampling.

div_phylo(x, tree, q = 1, ...)

# S3 method for numeric
div_phylo(
  x,
  tree,
  q = 1,
  normalize = TRUE,
  estimator = c("UnveilJ", "ChaoJost", "ChaoShen", "GenCov", "Grassberger", "Marcon",
    "UnveilC", "UnveiliC", "ZhangGrabchak", "naive", "Bonachela", "Holste"),
  level = NULL,
  probability_estimator = c("Chao2015", "Chao2013", "ChaoShen", "naive"),
  unveiling = c("geometric", "uniform", "none"),
  richness_estimator = c("jackknife", "iChao1", "Chao1", "naive"),
  jack_alpha = 0.05,
  jack_max = 10,
  coverage_estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
  as_numeric = FALSE,
  ...,
  check_arguments = TRUE
)

# S3 method for species_distribution
div_phylo(
  x,
  tree,
  q = 1,
  normalize = TRUE,
  estimator = c("UnveilJ", "ChaoJost", "ChaoShen", "GenCov", "Grassberger", "Marcon",
    "UnveilC", "UnveiliC", "ZhangGrabchak", "naive", "Bonachela", "Holste"),
  level = NULL,
  probability_estimator = c("Chao2015", "Chao2013", "ChaoShen", "naive"),
  unveiling = c("geometric", "uniform", "none"),
  richness_estimator = c("jackknife", "iChao1", "Chao1", "naive"),
  jack_alpha = 0.05,
  jack_max = 10,
  coverage_estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
  gamma = FALSE,
  ...,
  check_arguments = TRUE
)

Arguments

x

An object, that may be a numeric vector containing abundances or probabilities, or an object of class abundances or probabilities.

tree

An ultrametric, phylogenetic tree. May be an object of class phylo_divent, ape::phylo, ade4::phylog or stats::hclust.

q

The order of diversity.

...

Unused.

normalize

If TRUE, phylogenetic is normalized: the height of the tree is set to 1.

estimator

An estimator of asymptotic diversity.

level

The level of interpolation or extrapolation. It may be a sample size (an integer) or a sample coverage (a number between 0 and 1). If not NULL, the asymptotic estimator is ignored.

probability_estimator

A string containing one of the possible estimators of the probability distribution (see probabilities). Used only for extrapolation.

unveiling

A string containing one of the possible unveiling methods to estimate the probabilities of the unobserved species (see probabilities). Used only for extrapolation.

richness_estimator

An estimator of richness to evaluate the total number of species, see div_richness. Used for interpolation and extrapolation.

jack_alpha

The risk level, 5% by default, used to optimize the jackknife order.

jack_max

The highest jackknife order allowed. Default is 10.

coverage_estimator

An estimator of sample coverage used by coverage.

as_numeric

If TRUE, a number or a numeric vector is returned rather than a tibble.

check_arguments

If TRUE, the function arguments are verified. Should be set to FALSE to save time when the arguments have been checked elsewhere.

gamma

If TRUE, \(\gamma\) diversity, i.e. diversity of the metacommunity, is computed.

Value

A tibble with the site names, the estimators used and the estimated diversity

Details

Bias correction requires the number of individuals. See div_hill for estimators.

Entropy can be estimated at a specified level of interpolation or extrapolation, either a chosen sample size or sample coverage (Chao et al. 2014) , rather than its asymptotic value. See accum_tsallis for details.

References

Chao A, Gotelli NJ, Hsieh TC, Sander EL, Ma KH, Colwell RK, Ellison AM (2014). “Rarefaction and Extrapolation with Hill Numbers: A Framework for Sampling and Estimation in Species Diversity Studies.” Ecological Monographs, 84(1), 45--67. doi:10.1890/13-0133.1 .

Examples

div_phylo(paracou_6_abd, tree = paracou_6_taxo, q = 2)
#> # A tibble: 4 × 4
#>   site      weight estimator diversity
#>   <chr>      <dbl> <chr>         <dbl>
#> 1 subplot_1   1.56 UnveilJ        17.7
#> 2 subplot_2   1.56 UnveilJ        21.3
#> 3 subplot_3   1.56 UnveilJ        20.5
#> 4 subplot_4   1.56 UnveilJ        16.4

# At 80% coverage
div_phylo(paracou_6_abd, tree = paracou_6_taxo, q = 2, level = 0.8)
#> # A tibble: 4 × 4
#>   site      weight estimator diversity
#>   <chr>      <dbl> <chr>         <dbl>
#> 1 subplot_1   1.56 UnveilJ        14.4
#> 2 subplot_2   1.56 UnveilJ        17.7
#> 3 subplot_3   1.56 UnveilJ        16.7
#> 4 subplot_4   1.56 UnveilJ        14.0

# Gamma entropy
div_phylo(paracou_6_abd, tree = paracou_6_taxo, q = 2, gamma = TRUE)
#> # A tibble: 1 × 3
#>   site          estimator diversity
#>   <chr>         <chr>         <dbl>
#> 1 Metacommunity UnveilJ        19.7